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The elements of statistics for clinical readers

A J Hartz¹, R L Holloway

¹Department of Family and Community Medicine, Medical College of Wisconsin, Milwaukee, USA.

Archives of Family Medicine

|December 1, 1995

Summary

Understanding the purpose of statistical methods, not their math, is key for interpreting clinical studies. This approach focuses on evaluating risk factor-outcome associations and their clinical relevance.

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Area of Science:

Biostatistics
Clinical Research Methodology
Epidemiology

Background:

Traditional statistical courses prioritize mathematical properties of significance testing.
Clinical study interpretation requires understanding the purpose of statistical methods, not their complex mathematical underpinnings.

Purpose of the Study:

To shift focus from mathematical details to the functional purpose of statistical methods in clinical research.
To enhance the interpretability of clinical studies for readers by emphasizing the 'why' behind statistical analyses.

Main Methods:

The study outlines five key components for evaluating the association between risk factors and outcomes.
These components include measuring association strength, assessing statistical significance, determining confidence intervals, addressing confounding, and examining effect modification.

Main Results:

Focusing on the purpose of statistical evaluation simplifies interpretation for clinicians.
This approach reduces distractions from complex mathematical formulations that offer limited additional clinical insight.

Conclusions:

Emphasizing the purpose of statistical methods improves the practical application of clinical study findings.
Clinicians can better evaluate associations and their implications by understanding the goals of statistical analysis.

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